Machine intelligence for chemical reaction space
Discovering new reactions, optimizing their performance, and extending the synthetically
accessible chemical space are critical drivers for major technological advances and more …
accessible chemical space are critical drivers for major technological advances and more …
Automation and computer-assisted planning for chemical synthesis
The molecules of today—the medicines that cure diseases, the agrochemicals that protect
our crops, the materials that make life convenient—are becoming increasingly sophisticated …
our crops, the materials that make life convenient—are becoming increasingly sophisticated …
[HTML][HTML] Machine learning in chemical engineering: strengths, weaknesses, opportunities, and threats
Chemical engineers rely on models for design, research, and daily decision-making, often
with potentially large financial and safety implications. Previous efforts a few decades ago to …
with potentially large financial and safety implications. Previous efforts a few decades ago to …
Organic reactivity from mechanism to machine learning
As more data are introduced in the building of models of chemical reactivity, the mechanistic
component can be reduced until 'big data'applications are reached. These methods no …
component can be reduced until 'big data'applications are reached. These methods no …
Machine learning force fields: Recent advances and remaining challenges
In chemistry and physics, machine learning (ML) methods promise transformative impacts by
advancing modeling and improving our understanding of complex molecules and materials …
advancing modeling and improving our understanding of complex molecules and materials …
Inferring experimental procedures from text-based representations of chemical reactions
The experimental execution of chemical reactions is a context-dependent and time-
consuming process, often solved using the experience collected over multiple decades of …
consuming process, often solved using the experience collected over multiple decades of …
Into the unknown: how computation can help explore uncharted material space
Novel functional materials are urgently needed to help combat the major global challenges
facing humanity, such as climate change and resource scarcity. Yet, the traditional …
facing humanity, such as climate change and resource scarcity. Yet, the traditional …
Predicting reaction conditions from limited data through active transfer learning
Transfer and active learning have the potential to accelerate the development of new
chemical reactions, using prior data and new experiments to inform models that adapt to the …
chemical reactions, using prior data and new experiments to inform models that adapt to the …
Intensification of catalytic reactors: a synergic effort of multiscale modeling, machine learning and additive manufacturing
M Bracconi - Chemical Engineering and Processing-Process …, 2022 - Elsevier
The intensification of catalytic reactors is expected to play a crucial role to address the
challenges that the chemical industry is facing in the transition to more sustainable …
challenges that the chemical industry is facing in the transition to more sustainable …
A review on artificial intelligence enabled design, synthesis, and process optimization of chemical products for industry 4.0
With the development of Industry 4.0, artificial intelligence (AI) is gaining increasing attention
for its performance in solving particularly complex problems in industrial chemistry and …
for its performance in solving particularly complex problems in industrial chemistry and …